The imaging core for the program project grant ?Frontotemporal Dementia: Genes, Images and Emotions? has managed the acquisition, storage, distribution and analysis of brain imaging data since the initial funding of the grant. Throughout the life of the project, the imaging core has ensured that images are properly acquired, uniform in quality and that raw and processed images are shared with other PPG researchers and with the other scientific collaborators. The imaging core has also led the development of many new processing pipelines to support the scientific goals of the PPG. For the proposed fourth cycle of this PPG, the imaging core will pursue the following aims: 1) Collection and archiving of images and maintenance of an image database: We will collect and manage the following MRI sequences in age-matched patients with bvFTD, nfvPPA, svPPA, CBS, PSPS, lvPPA, AD and age-matched participants with major depressive disorder (MDD) and bipolar affective disorder (BAD): MP-RAGE, FLAIR, dMRI, ASL perfusion, tf-fMRI and T2-weighted MRI. We will also acquire [18F]AV-1451 and [11C]PIB PET scans. Working with the data management core, we will archive de-identified images on a server accessible to the rest of the PPG investigators and provide tools for locating and retrieving images for analysis. 2) Image preprocessing: We will preprocess MR images including RF field bias and geometrical distortion corrections. We will coregister each subject's dMRI, ASL, tf-fMRI and PET images to their ?native space? as defined by their MPRAGE, 3) Extraction of regional volumetric and molecular data and creation of longitudinal change maps: We will process T1-weighted images with SPM to derive regional gray matter volumes using standard cortical and subcortical regions of interest (ROIs). We will derive regional tau PET and normalized amyloid tracer binding values for standard ROIs. We will create voxel- wise maps for subjects with bvFTD, nfvPPA, svPPA, CBS, PSPS, lvPPA, AD, MDD and BAD quantifying 1- year change in gray matter volume and tau PET signal (for those undergoing longitudinal imaging) in native and standard spaces. Working with the data management core, we will make these values and maps available to other PPG researchers on a secure server, and 4) Consultation on analysis: We will work with PIs and staff serving the other PPG projects and cores on incorporating these and other imaging data into their analyses.
Brain imaging plays a critical role in research and clinical assessment of frontotemporal dementia and related disoders. The role of the imaging core for the program project grant entitled ?Frontotemporal dementia: Genes, Images and Emotions? is to ensure that images used by other researchers on the project are uniformly high in quality and easily accessible, and that various procedures for analyzing the images are available for use by all researchers.
| Miller, Zachary A; Rosenberg, Lynne; Santos-Santos, Miguel A et al. (2018) Prevalence of Mathematical and Visuospatial Learning Disabilities in Patients With Posterior Cortical Atrophy. JAMA Neurol 75:728-737 |
| Rojas, Julio C; Stephens, Melanie L; Rabinovici, Gil D et al. (2018) Multiproteinopathy, neurodegeneration and old age: a case study. Neurocase 24:1-6 |
| Dijkstra, Anke A; Lin, Li-Chun; Nana, Alissa L et al. (2018) Von Economo Neurons and Fork Cells: A Neurochemical Signature Linked to Monoaminergic Function. Cereb Cortex 28:131-144 |
| Mok, Sue-Ann; Condello, Carlo; Freilich, Rebecca et al. (2018) Mapping interactions with the chaperone network reveals factors that protect against tau aggregation. Nat Struct Mol Biol 25:384-393 |
| Erkkinen, Michael G; Zúñiga, Raquel Gutiérrez; Pardo, Cristóbal Carnero et al. (2018) Artistic Renaissance in Frontotemporal Dementia. JAMA 319:1304-1306 |
| Schneider, Raphael; McKeever, Paul; Kim, TaeHyung et al. (2018) Downregulation of exosomal miR-204-5p and miR-632 as a biomarker for FTD: a GENFI study. J Neurol Neurosurg Psychiatry 89:851-858 |
| Ljubenkov, Peter A; Staffaroni, Adam M; Rojas, Julio C et al. (2018) Cerebrospinal fluid biomarkers predict frontotemporal dementia trajectory. Ann Clin Transl Neurol 5:1250-1263 |
| La Joie, Renaud; Bejanin, Alexandre; Fagan, Anne M et al. (2018) Associations between [18F]AV1451 tau PET and CSF measures of tau pathology in a clinical sample. Neurology 90:e282-e290 |
| Kim, Eun-Joo; Brown, Jesse A; Deng, Jersey et al. (2018) Mixed TDP-43 proteinopathy and tauopathy in frontotemporal lobar degeneration: nine case series. J Neurol 265:2960-2971 |
| Henry, Maya L; Hubbard, H Isabel; Grasso, Stephanie M et al. (2018) Retraining speech production and fluency in non-fluent/agrammatic primary progressive aphasia. Brain 141:1799-1814 |
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